DP-600 Question #40: Real Exam Question with Answer & Explanation

Question

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have a Fabric tenant that contains a new semantic model in OneLake. You use a Fabric notebook to read the data into a Spark DataFrame. You need to evaluate the data to calculate the min, max, mean, and standard deviation values for all the string and numeric columns. Solution: You use the following PySpark expression: df.explain() Does this meet the goal?

Options

• AYes
• BNo

Explanation

The df.explain() PySpark expression does not calculate descriptive statistics like min, max, mean, and standard deviation.

Common mistakes.

• A. df.explain() provides query plan details, not statistical summaries of data content.

Concept tested. PySpark DataFrame query plan inspection

Reference. https://spark.apache.org/docs/latest/api/python/reference/api/pyspark.sql.DataFrame.explain.html

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